✨ Introduction

This is an opinionated tool for testing MCP servers live.

You point it at a live MCP server with streaming response, and it:

• Queries HTTP endpoints (/mcp)
• Lists available tools
• Validates that tools have descriptions

pytest --mcp-tools=http://localhost:8000

🔍 MCP Tools: Discovering endpoints at http://docker-image:8000...
   Checking http://docker-image:8000...
   ✓ Server reachable (status: 404)
   ✓ Found endpoint: /mcp (status: 200)
   ✗ Endpoint /sse not found (status: 404)
   ✗ Endpoint /messages not found (status: 404)
🔍 MCP Tools: Checking STDIO support for docker-image...
   ✓ STDIO communication successful (3 tool(s) found)
✅ MCP Tools: Discovered endpoints: /mcp

============================= test session starts ==============================
platform linux -- Python 3.11.14, pytest-9.0.2, pluggy-1.6.0 -- /usr/local/bin/python
cachedir: .pytest_cache
rootdir: /app
configfile: pyproject.toml
plugins: mcp-tools-0.1.2, anyio-4.12.1
collecting ... collected 0 items

created 6 tests
✅ MCP tools test created for discovered endpoints: /mcp
   📡 HTTP streaming support detected
   📡 STDIO transport support detected

..::test_mcp_tools[POST /mcp] PASSED                                     [ 16%]
..::test_list_tools_from_basic_server PASSED                             [ 33%]
..::test_tools_have_descriptions PASSED                                  [ 50%]
..::test_tools_have_names PASSED                                         [ 66%]
..::test_tools_have_unique_names PASSED                                  [ 83%]
..::test_list_tools_via_stdio PASSED                                     [100%]

============================== 6 passed in 2.62s ===============================

Features

Automated Tests

The plugin generates tests to verify:

• At least one transport is available (HTTP or STDIO)
• Tools can be listed successfully
• All tools have description fields

Later versions will include:

• Call the tools, based on annotations.
• Check the responses from the tools against outputSchema
• Token count limiting checks
• LLM-as-a-Judge checks to validate description quality
• oAuth and perhaps CORS, as needed. (This is not strictly necessary, because I am imagining that this is going run as a staging test in an environment where all servers are trusted.)

Reporting Issues

If you tested this on your server, and think that there is an issue, just give me the docker image of your server in the issue, and tell me what you are expecting, what you got.

If you don't have a docker hub image, give me a minimal example. That's all I need.

🛠️ Development

The only requirement is 🐳 Docker. (The .devcontainer and tasks.json are prepared assuming a *nix system, but if you know the commands, this will work on Windows, too.)

1. Clone the repo.
2. Branch out.
3. Open in "devcontainer" on VS Code and start developing. Run pytest under tests to test.
4. Akternatively, if you are a fan of Test-Driven Development like me, you can run the tests without getting on a container. .vscode/tasks.json has the command to do so, but it's also listed here:

docker compose -f tests/docker-compose.yaml up --build --abort-on-container-exit --exit-code-from test